Introduction: Acute promyelocytic leukemia (APML), although genetically and morphologically distinct from other AML (acute myeloid leukemia) subtypes, is one of the most best responsive acute myeloid leukemia. -Conventional diagnostic methods and morphological hints often fail in the majority of the cases in the peripheral laboratories owing to resource constraints, unavailability of cytogenetic work-up, hypogranular variants, morphological mimicry by AML-monocytic and myelo-monocytic, etc. Flowcytometry (FCM), however, can be utilized as a feasible and reliable immunophenotypic diagnostic and prognostic tool for prompt identification of APML. In order to rapidly and sensitively diagnose APML we intended to suggest a cost effective, sensitive FCM panel and also to prognositicate patients., Material and Methods: In this retrospective study, flowcytometry characteristics of 123 cases of acute promyelocytic leukemia were studied including 40 hypogranular variants. The expression of markers was compared with the Mean flurescent Intensity (MFI) and percent expression of markers. A non-statistical comparison was made with cases of acute monocytic leukemia. The cases were grouped according to their immunophenotype characteristics and expression with comparison of MFI by multivariate logistic regression. The aberrant markers positive at diagnostic and remission flow test were compared with the survival outcomes, and their positive predictive values were calculated., Results: The most common feature of side scatter property was the absence of blasts in the window and high side scatter, except hypogranular variants which had low side scatter. Immunophenotypically characterised by positivity for CD117, cMPO, and bright CD33 and CD13 positivity and lack of CD34 and HLA-DR was seen in the majority of APML including hypo-granular variant. We suggest a rapid diagnostic four-tube panel for fast and rapid diagnosis of APML, including hypogranular variants with 100% sensitivity. The study also identified six groups of immunophenotypes with significant prediction values of APML, including hypogranular variants. The study also highlights CD2, CD56, and CD9 as prognostic markers for acute promyelocytic leukemia., Competing Interests: A retrospective study from 2014-2019 of all the cases of APML after obtaining consent from patients/guardians were evaluated for clinicopathological parameters, flow cytometry, and cytochemistry. Reverse transcriptase PCR (RT-PCR) for PML-RAR alpha was done from private labs by outsourcing in cases with clinical suspicion or where-ever possible. Routine molecular cytogenetic studies for APL specific performed by standard G-banding techniques on unstimulated culture. Inclusion criteriaCases of untreated acute leukemia that attended the OPDs of AIIMS and VMMC and SJH hospital in pediatric OPDs which were diagnosed as APML and decided to continue treatment in the same centre. Cases that had given consent to participate in the study.Exclusion criteriaCases which had been partially treated outside, cases which did not continue treatment at the same centre, cases which showed reactivity to HIV/HCV and HBsAg were excluded from the study. Also, cases in which consent could not be obtained were excluded from study. Four-color FCM analysis was performed for all cases using BD FACS Calibur and BC FC500, and the data were analyzed with FACS DIVA software (BD Biosciences, San Jose, CA) in accordance with the international consensus recommendations on flowcytometric analysis of hematolymphoid neoplasia [5]. The antibodies in our routine panel included shown in Table 1 apart from the screening cytoplasmic tube for the exclusion of lymphoid and other myeloid neoplasms. The gating strategy was followed as published before [6]. The percent positivity taken for the categorization of negative, dim positive, and positive is mentioned in Table 1, along with the clone utilized during the experimentation. For the purpose of comparing our results with the literature, we arbitrarily defined in this study staining of 20% or more positivity for the markers like CD34, HLA-DR, CD33, CD13, etc. The minimum positive blast population and the criterion for dim positivity to be considered as positive being mentioned in the table along with other immunomarkers. We then analyzed the immunophenotypic profiles of these cases in relation to individual antigen expression and karyotype findings. The aberrant markers positive at diagnostic and remission flow test were compared with the survival outcomes, and their positive predictive values were calculated with the ability for the exclusion of other diagnosis from APML by comparing the immunophenotypic results with a different series of AML cases (control for statistical analysis). Clinical management protocol as per NCCN update Version 2.2014 (Annexure 1). Clinical outcomes: As per the standard definitions of CR, OS, RFS, and EFS [2] (Annexure 2), Statistical analysis. Table 1Flow markers with clone and distribution of positivityS No.CD MarkerConjugateCloneMin Positive Population percentDim PositiveMean MFI Normal/Blast1CD34PC5.5Immu13320100.42/0.722CD117PC7104D2D120100.20/0.353HLA-DRPacific blueImmu-35720104.33/0.544CD2ECD39C1.510105.18/1.055CD3APC 750UCHT1101016.77/1.346CD7APC8H8.1101028.63/0.107CD9APC 750ALB615150.46/62.468CD11bAPCBear115158.29/3.309CD11cPC7BU1515150.32/0.7010CD13ECDSJ1D120150.20/9.3411CD14APC 750RMO5220200.31/0.9112CD16FITC3G820200.22/1.0513CD18PE7E420200.68/0.7614CD33APCD3HL60.25120150.40/35.5415CD56PEN90120200.29/0.2216CD64ECD2220200.44/5.4217CD65FITC88H720200.20/0.5618cMPO*FITCCLB-MPO-103200.93/3.67*Any positive percent was reported independently regardless of the threshold.Statistical analysisAnalysis was done on the patients who consented for the study and for treatment. Fisher exact test was used to compare differences between groups with respect to clinicopathological characteristics, clinical outcomes, and response to therapy. The probability of survival was estimated with the use of the Kaplan and Meier method for overall survival, event-free survival and disease-free survival and compared by the log-rank test among risk groups. All survival estimates are reported ± 1 SE. All P values were two-sided, with values of 0.05 or less indicating a statistical significance. All statistical analyses were performed using SPSS v.16.0 software (SPSS Inc., Chicago, USA). Clinical features are presented as percentages (%) for categorical variables and as mean values ± standard deviation (SD) for normally distributed continuous variables. The chi 2 test was used to analyze differences in the distribution of categorical variables between patient subsets. The Chi 2 test was used to detect differences in the distribution of continuous parametric variables. Multivariateanalyses were performed using a multiple logistic regression analysis. P values <0.05 were considered statistically significant. A cutoff of >10% was used to quantify the presence of a subpopulation of CD34+ and CD56+ cells, and a cutoff of >20% was used for defining positivity for CD34, CD33, CD56 as mentioned in Table 1. Table 2Immunophenotypic characteristicsCasesNo.HLA DRCD33CD13CD34#cMPO*CD11b$CD11c@CD117CD9CD56CD2CD15All APL cases12317 (13.8)123 (100)122 (99.1)30 (24.4%)123 (100)2612122 (99.1)120183040Hyper granular variant831283 (100)82 (98.7)15 (18.1)83 (100)18 (21.7)1182 (98.7)80101327Hypo Granular Variant405 (12.5)40 (100)40 (100)15 (37.5)40 (100)8 (20.0)8 (20.0)40 (100)40 (100)8 (20.0)1713AML M4/M560404937545855524201390245#including heterogenous positive population.*Considered positive even if the threshold for 3% population of interest is present.$co-positivity for CD117 required to distinguish maturing myeloid precursors or granular monocytes includes dim positivity.@Indicates positivity if more than 5% of population shows moderate to bright positivityNone., (AJBR Copyright © 2021.)